924 research outputs found
Improving Approximate Pure Nash Equilibria in Congestion Games
Congestion games constitute an important class of games to model resource
allocation by different users. As computing an exact or even an approximate
pure Nash equilibrium is in general PLS-complete, Caragiannis et al. (2011)
present a polynomial-time algorithm that computes a ()-approximate pure Nash equilibria for games with linear cost
functions and further results for polynomial cost functions. We show that this
factor can be improved to and further improved results for
polynomial cost functions, by a seemingly simple modification to their
algorithm by allowing for the cost functions used during the best response
dynamics be different from the overall objective function. Interestingly, our
modification to the algorithm also extends to efficiently computing improved
approximate pure Nash equilibria in games with arbitrary non-decreasing
resource cost functions. Additionally, our analysis exhibits an interesting
method to optimally compute universal load dependent taxes and using linear
programming duality prove tight bounds on PoA under universal taxation, e.g,
2.012 for linear congestion games and further results for polynomial cost
functions. Although our approach yield weaker results than that in Bil\`{o} and
Vinci (2016), we remark that our cost functions are locally computable and in
contrast to Bil\`{o} and Vinci (2016) are independent of the actual instance of
the game
On Existence and Properties of Approximate Pure Nash Equilibria in Bandwidth Allocation Games
In \emph{bandwidth allocation games} (BAGs), the strategy of a player
consists of various demands on different resources. The player's utility is at
most the sum of these demands, provided they are fully satisfied. Every
resource has a limited capacity and if it is exceeded by the total demand, it
has to be split between the players. Since these games generally do not have
pure Nash equilibria, we consider approximate pure Nash equilibria, in which no
player can improve her utility by more than some fixed factor through
unilateral strategy changes. There is a threshold (where
is a parameter that limits the demand of each player on a specific
resource) such that -approximate pure Nash equilibria always exist for
, but not for . We give both
upper and lower bounds on this threshold and show that the
corresponding decision problem is -hard. We also show that the
-approximate price of anarchy for BAGs is . For a restricted
version of the game, where demands of players only differ slightly from each
other (e.g. symmetric games), we show that approximate Nash equilibria can be
reached (and thus also be computed) in polynomial time using the best-response
dynamic. Finally, we show that a broader class of utility-maximization games
(which includes BAGs) converges quickly towards states whose social welfare is
close to the optimum
Efficient computation of approximate pure Nash equilibria in congestion games
Congestion games constitute an important class of games in which computing an
exact or even approximate pure Nash equilibrium is in general {\sf
PLS}-complete. We present a surprisingly simple polynomial-time algorithm that
computes O(1)-approximate Nash equilibria in these games. In particular, for
congestion games with linear latency functions, our algorithm computes
-approximate pure Nash equilibria in time polynomial in the
number of players, the number of resources and . It also applies to
games with polynomial latency functions with constant maximum degree ;
there, the approximation guarantee is . The algorithm essentially
identifies a polynomially long sequence of best-response moves that lead to an
approximate equilibrium; the existence of such short sequences is interesting
in itself. These are the first positive algorithmic results for approximate
equilibria in non-symmetric congestion games. We strengthen them further by
proving that, for congestion games that deviate from our mild assumptions,
computing -approximate equilibria is {\sf PLS}-complete for any
polynomial-time computable
Strong Nash Equilibria in Games with the Lexicographical Improvement Property
We introduce a class of finite strategic games with the property that every
deviation of a coalition of players that is profitable to each of its members
strictly decreases the lexicographical order of a certain function defined on
the set of strategy profiles. We call this property the Lexicographical
Improvement Property (LIP) and show that it implies the existence of a
generalized strong ordinal potential function. We use this characterization to
derive existence, efficiency and fairness properties of strong Nash equilibria.
We then study a class of games that generalizes congestion games with
bottleneck objectives that we call bottleneck congestion games. We show that
these games possess the LIP and thus the above mentioned properties. For
bottleneck congestion games in networks, we identify cases in which the
potential function associated with the LIP leads to polynomial time algorithms
computing a strong Nash equilibrium. Finally, we investigate the LIP for
infinite games. We show that the LIP does not imply the existence of a
generalized strong ordinal potential, thus, the existence of SNE does not
follow. Assuming that the function associated with the LIP is continuous,
however, we prove existence of SNE. As a consequence, we prove that bottleneck
congestion games with infinite strategy spaces and continuous cost functions
possess a strong Nash equilibrium
Equilibrium Computation in Resource Allocation Games
We study the equilibrium computation problem for two classical resource
allocation games: atomic splittable congestion games and multimarket Cournot
oligopolies. For atomic splittable congestion games with singleton strategies
and player-specific affine cost functions, we devise the first polynomial time
algorithm computing a pure Nash equilibrium. Our algorithm is combinatorial and
computes the exact equilibrium assuming rational input. The idea is to compute
an equilibrium for an associated integrally-splittable singleton congestion
game in which the players can only split their demands in integral multiples of
a common packet size. While integral games have been considered in the
literature before, no polynomial time algorithm computing an equilibrium was
known. Also for this class, we devise the first polynomial time algorithm and
use it as a building block for our main algorithm.
We then develop a polynomial time computable transformation mapping a
multimarket Cournot competition game with firm-specific affine price functions
and quadratic costs to an associated atomic splittable congestion game as
described above. The transformation preserves equilibria in either games and,
thus, leads -- via our first algorithm -- to a polynomial time algorithm
computing Cournot equilibria. Finally, our analysis for integrally-splittable
games implies new bounds on the difference between real and integral Cournot
equilibria. The bounds can be seen as a generalization of the recent bounds for
single market oligopolies obtained by Todd [2016].Comment: This version contains some typo corrections onl
Dynamic club formation with coordination
We present a dynamic model of jurisdiction formation in a society of identical people. The process is described by a Markov chain that is defined by myopic optimization on the part of the players. We show that the process will converge to a Nash equilibrium club structure. Next, we allow for coordination between members of the same club,i.e. club members can form coalitions for one period and deviate jointly. We define a Nash club equilibrium (NCE) as a strategy configuration that is immune to such coalitional deviations. We show that, if one exists, this modified process will converge to a NCE configuration with probability one. Finally, we deal with the case where a NCE fails to exist due to indivisibility problems. When the population size is not an integer multiple of the optimal club size, there will be left over players who prevent the process from settling down. We define the concept of an approximate Nash club equilibrium (ANCE), which means that all but k players are playing a Nash club equilibrium, where k is defined by the minimal number of left over players. We show that the modified process converges to an ergodic set of states each of which is ANCE
Efficient Equilibria in Polymatrix Coordination Games
We consider polymatrix coordination games with individual preferences where
every player corresponds to a node in a graph who plays with each neighbor a
separate bimatrix game with non-negative symmetric payoffs. In this paper, we
study -approximate -equilibria of these games, i.e., outcomes where
no group of at most players can deviate such that each member increases his
payoff by at least a factor . We prove that for these
games have the finite coalitional improvement property (and thus
-approximate -equilibria exist), while for this
property does not hold. Further, we derive an almost tight bound of
on the price of anarchy, where is the number of
players; in particular, it scales from unbounded for pure Nash equilibria ( to for strong equilibria (). We also settle the complexity
of several problems related to the verification and existence of these
equilibria. Finally, we investigate natural means to reduce the inefficiency of
Nash equilibria. Most promisingly, we show that by fixing the strategies of
players the price of anarchy can be reduced to (and this bound is tight)
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